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3D Shape Classification

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Showing 1–50 of 82 papers

TitleStatusHype
Interpretable3D: An Ad-Hoc Interpretable Classifier for 3D Point CloudsCode1
ViPFormer: Efficient Vision-and-Pointcloud Transformer for Unsupervised Pointcloud UnderstandingCode1
MVTN: Learning Multi-View Transformations for 3D UnderstandingCode1
PointMCD: Boosting Deep Point Cloud Encoders via Multi-view Cross-modal Distillation for 3D Shape RecognitionCode1
Masked Discrimination for Self-Supervised Learning on Point CloudsCode1
diffConv: Analyzing Irregular Point Clouds with an Irregular ViewCode1
DSPoint: Dual-scale Point Cloud Recognition with High-frequency FusionCode1
PolyNet: Polynomial Neural Network for 3D Shape Recognition with PolyShape RepresentationCode1
POINTVIEW-GCN: 3D SHAPE CLASSIFICATION WITH MULTI-VIEW POINT CLOUDSCode1
Spatio-temporal Self-Supervised Representation Learning for 3D Point CloudsCode1
Learning Equivariant RepresentationsCode1
MVTN: Multi-View Transformation Network for 3D Shape RecognitionCode1
View-GCN: View-Based Graph Convolutional Network for 3D Shape AnalysisCode1
Fine-Grained 3D Shape Classification with Hierarchical Part-View AttentionsCode1
Deep Learning for 3D Point Clouds: A SurveyCode1
A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation—0
Ensemble Quadratic Assignment Network for Graph Matching—0
Invariant Training 2D-3D Joint Hard Samples for Few-Shot Point Cloud Recognition—0
Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point CloudsCode0
Multi-View Representation is What You Need for Point-Cloud Pre-Training—0
APPT : Asymmetric Parallel Point Transformer for 3D Point Cloud Understanding—0
Frequency-domain Learning for Volumetric-based 3D Data Perception—0
Robust 3D Shape Classification via Non-Local Graph Attention Network—0
Rethinking Rotation Invariance with Point Cloud Registration—0
LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in TransformersCode0
VN-Transformer: Rotation-Equivariant Attention for Vector Neurons—0
PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds—0
TreeGCN-ED: Encoding Point Cloud using a Tree-Structured Graph NetworkCode0
Contrastive Learning of 3D Shape Descriptor with Dynamic Adversarial Views—0
Adaptive Wavelet Transformer Network for 3D Shape Representation Learning—0
Point Cloud Learning with Transformer—0
Potential Convolution: Embedding Point Clouds into Potential Fields—0
RocNet: Recursive Octree Network for Efficient 3D Deep Representation—0
Learning Attentive and Hierarchical Representations for 3D Shape Recognition—0
Unsupervised Deep Shape Descriptor With Point Distribution LearningCode0
Extending DeepSDF for automatic 3D shape retrieval and similarity transform estimation—0
Joint Supervised and Self-Supervised Learning for 3D Real-World Challenges—0
Self-supervised Feature Learning by Cross-modality and Cross-view Correspondences—0
Shape retrieval of non-rigid 3d human models—0
Enhancing 2D Representation via Adjacent Views for 3D Shape Retrieval—0
A Topological Nomenclature for 3D Shape Analysis in ConnectomicsCode0
HRGE-Net: Hierarchical Relational Graph Embedding Network for Multi-view 3D Shape Recognition—0
View N-gram Network for 3D Object Retrieval—0
Rethinking Loss Design for Large-scale 3D Shape Retrieval—0
Re-Ranking via Metric Fusion for Object Retrieval and Person Re-Identification—0
Deep Sketch-Shape Hashing With Segmented 3D Stochastic Viewing—0
Skeleton-Based Hand Gesture Recognition by Learning SPD Matrices with Neural Networks—0
Equivariant Multi-View NetworksCode0
Non-rigid 3D shape retrieval based on multi-view metric learning—0
A Sketch Based 3D Shape Retrieval Approach Based on Efficient Deep Point-to-Subspace Metric Learning—0
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